Forecasting volatility

被引：13
|
作者：
Thavaneswaran, A
Appadoo, SS
Peiris, S [1 ]
机构：
[1] Univ Sydney, Sch Math & Stat, Sydney, NSW 2006, Australia
[2] Univ Manitoba, Dept Stat, Winnipeg, MB R3T 2N2, Canada
来源：
STATISTICS & PROBABILITY LETTERS | 2005年 / 75卷 / 01期
关键词：
forecasting; GARCH models; Stochastic volatility; innovations; heteroscedasticity; random; conditional; expectation;
D O I：
10.1016/j.spl.2005.05.015
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
This paper studies the problem of volatility forecasting for some financial time series models. We consider several stochastic volatility models including GARCH, Power GARCH and non-stationary GARCH for illustration. In particular, a martingale representation is used to obtain the l-steps-ahead forecast error variance for the class of GARCH models. Some closed-form expressions for the variance of l-steps-ahead forecasts errors are given in terms of psi weights and the kurtosis of the error distribution. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：1 / 10
页数：10
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